Bengt, I am applying a 2-groups (males and females) version the status change model described in “The Influence of Changes in Marital Status on Developmental Trajectories of Alcohol Use in Young Adults” (Curran and colleagues, 1998). I have 2 clarification questions: 1-- In your analysis, all of the status change coefficients were significant and of comparable magnitude. How would one interpret model results where only some (one out of 3 in my case) of the status change coefficients are significant? 2-- Regarding interactions: while I understand the intuition behind testing against the grand mean effect model as described in the paper, why not simply test the 2-group unconstrained model (model 2 in the paper) against a model that imposes equality on the 3 intercept terms across groups? Thanks!

Thank you for your answer. I have a couple more questions: 1--In discussing possible extensions to this model, the paper states "the status change variables can be cumulative (e.g. once married always married)". What would be the interpretation of the coefficients on such a variable? 2-- I am considering an extension to this model which would use the duration (in months) since the status change occurred rather than the status change variable itself. I am interested in seeing whether the effect of status change on the added intercept diminishes with time since event occurrence. Would this be an appropriate way to do this? Thank you for your help.

I am attempting to test a model similar to Curran, Muthen & Harford (1998).

Can you tell me how to develop syntax to create a latent intercept factor representing change in status at each time point?

This is the syntax I'm currently using for this model but I am not sure it gets at what Curran et al. do in their article. I want to know how change in school status at each time point is associated with change in depressive symptoms at each time.